Method, medium, and system for reducing counterfeits online

ABSTRACT

Systems and methods change a user interface for the purpose of guiding a user in supplementing a product listing with an image to evidence the product&#39;s authenticity. Example embodiments include a machine-implemented method for accessing at least one database to retrieve an authenticity criterion mapped to a product and at least one reference image that depicts adequate detail of a product specimen to fulfill the authenticity criterion. The machine can further cause a user device to display the reference image to the user along with a suggestion that the user submit a candidate image depicting similar detail of the product. In some example embodiments, the method further includes retrieving the candidate image, confirming receipt of the candidate image, and displaying the candidate image, as well as adjusting a rank for a candidate specimen based on various factors.

CLAIM OF PRIORITY

This application is a continuation of and claims priority to U.S.application Ser. No. 16/162,367, filed Oct. 16, 2018, which is acontinuation of U.S. application Ser. No. 14/962,399, filed Dec. 8,2015. The contents of these prior applications are considered part ofthis application, and are hereby incorporated by reference in theirentirety.

TECHNICAL FIELD

The subject matter disclosed herein generally relates to the technicalfield of special-purpose machines that provide guidance to usersincluding computerized variants of such special-purpose machines andimprovements to such variants, and to the technologies by which suchspecial-purpose machines become improved compared to otherspecial-purpose machines that provide guidance to users. Specifically,the present disclosure addresses a guided listing machine withauthenticity support.

BACKGROUND

A machine may be configured to interact with one or more users byallowing the users to publish an offer of availability of one or moreitems over a network. The machine may be further configured to assistthe users in procuring the items with previously published availability.The machine may further have access to and communicate with variousdatabases, the databases containing information about the physicalcharacteristics of various products.

Due to the potential vastness of availability and demand for specificitems, procuring users generally desire to minimize their risk forprocuring counterfeit items and may be more nervous about counterfeitswhen purchasing from individuals rather than large retail chains. Thevalue of an item or the likelihood that a procuring user might desire toprocure the item over similar items may rise if evidence attesting tothe authenticity of an item is added.

BRIEF DESCRIPTION OF THE DRAWINGS

Some example embodiments are illustrated by way of example and notlimitation in the figures of the accompanying drawings.

FIG. 1 is a network diagram illustrating a network environment suitablefor a guided listing machine with authenticity support, according tosome example embodiments.

FIG. 2 is a block diagram illustrating components of a guided listingmachine with authenticity support, according to some exampleembodiments.

FIGS. 3-5 are flowcharts illustrating operations of the guided listingmachine in performing a method of guiding a listing and providingauthenticity support, according to some example embodiments.

FIGS. 6-9 are illustrations of the device interacting with a user toguide the user in listing a product and providing authenticity supportby providing a reference image and a suggestion and guiding the user insubmitting a candidate image, according to some example embodiments.

FIG. 10 is a block diagram illustrating components of a machine,according to some example embodiments, able to read instructions from amachine-readable medium and perform any one or more of the methodologiesdiscussed herein.

DETAILED DESCRIPTION

Example methods (e.g., algorithms) facilitate a guided listing systemwith authenticity support, and example systems (e.g., special-purposemachines) are configured to facilitate guided listing with authenticitysupport. Examples merely typify possible variations. Unless explicitlystated otherwise, structures (e.g., structural components, such asmodules) are optional and may be combined or subdivided, and operations(e.g., in a procedure, algorithm, or other function) may vary insequence or be combined or subdivided. In the following description, forpurposes of explanation, numerous specific details are set forth toprovide a thorough understanding of example embodiments. It will beevident to one skilled in the art, however, that the present subjectmatter may be practiced without these specific details.

In various example embodiments, a guided listing machine withauthenticity support receives a request from a user to publish theavailability of a specimen of a product, access a database that containsat least one authenticity criterion that can be mapped onto the product.The guided listing machine further retrieves at least one referenceimage that depicts the product and fulfills the authenticity criterionfrom an image database, generates an alert that contains the referenceimage and a suggestion that the user submit a candidate image that alsofulfills the authenticity criterion, and presents the alert to the user.

In more detail, the guided listing machine receives a request to publishthe availability of a candidate specimen of a product responsive to theuser designating the product that they would like to offer. This mayinclude receiving various information from the user, such as a producttitle, description, price, and even a product image. Based on thisinformation, the user is able to designate the specific type of productthat the user is trying to list. The user may further designate theproduct to be offered by selecting information from a list of producttitles or images.

Next, the guided listing machine accesses a database that contains atleast one authenticity criterion that is mapped to the product that isassociated with the request. This database may contain one or moreauthenticity criteria that identify one or more reference detailsphysically present in the product that attest to the product being anauthentic version rather than a counterfeit or a completely differentproduct.

The guided listing machine further accesses a database that contains atleast one reference image that depicts a reference detail, the referencedetail fulfilling the authenticity criterion mapped to the product. Thereference image may depict the entire product or a portion of theproduct. In the event that the product has multiple reference detailsassociated with one or more authenticity criteria, more than one imagedatabase may be accessed to receive reference images.

Next, the guided listing machine generates an alert, the alertcontaining at least one reference image depicting at least one referencedetail that supports the authenticity of the product, and a suggestionthat the user submit a candidate image that similarly depicts referencedetails depicted in the reference image. The suggestion can additionallyinclude at least one benefit of uploading a candidate image.

After generating the alert, the guided listing machine causes the alertto be presented to the user. The alert may be presented on a the displayof a user device. The alert may further include multiple options, suchas an method of submitting the candidate image.

In other example embodiments, the guided listing machine may receive acandidate image from the user, display a confirmation that the image hasbeen received successfully, and display the candidate image in the samewindow as the reference image.

In other example embodiments, the guided listing machine adjust a rankof the candidate specimen, the rank being adjusted based on one or morefactors, such as: whether the user has uploaded a candidate imageassociated with the candidate image, whether the candidate specimen ispart of a collection of items, whether the user has a history ofuploading candidate images in response to suggestions, and whether theuser has uploaded a candidate image that directly matches an imagealready contained in a database accessible by the guided listingmachine. The guided listing machine may determine this direct match bylocating a copy identifier within the data of a candidate image.

FIG. 1 is a network diagram illustrating a network environment 100suitable for a guided listing system with authenticity support,according to some example embodiments. The network environment 100includes a guided listing machine 110, a product database 115, an imagedatabase 116, a user history database 117, an offering user device 130,and a procuring user device 150, all communicatively coupled to eachother via a network 190. The guided listing machine 110, with or withoutone or more of the databases 115, 116 or 117, may form all or part of acloud 118 (e.g., a geographically distributed set of multiple machinesconfigured to function as a single server), which may form all or partof a network-based system 105 (e.g., a cloud-based server systemconfigured to provide one or more network-based services to the offeringuser device 130 and the procuring user device 150). The guided listingmachine 110, the offering user device 130, and the procuring user device150 may each be implemented in a special-purpose (e.g., specialized)computer system, in whole or in part, as described below with respect toFIG. 10.

The guided listing machine 110 guides a user in offering a product, theguiding including providing an example of a detail that fulfills anauthenticity criterion and suggestion that the user submit a candidateimage that fulfills the authenticity criterion. In an exampleembodiment, the guided listing machine 110 is capable of communicationswith the databases 115, 116, and 117 over the network 190 as well ascommunications with the offering user device 130 and the procuring userdevice 150 over the network 190.

For example, the product database 115 may communicate with the guidedlisting machine 110 by transmitting information about a reference detailin response to a request from the guided listing machine 110, thecommunications occurring over the network 190. The reference detail caninclude any characteristic that is visually apparent on a product, suchas an embossed patch of leather with a brand logo on the handle of ahandbag. The image database 116 and the user history database 117 maysimilarly communicate with guided listing machine 110 to providecommunications (e.g., data transfer) of information, such as referenceimages, over the network 190. The offering user device 130 and theprocuring user device 150 may further receive communications from anyone or more of the databases 115, 116, or 117 as well as guided listingmachine 110 over the network 190.

Also shown in FIG. 1 are an offering user 132 and a procuring user 152.One or both of the offering user 132 and the procuring user 152 may be ahuman user (e.g., a human being), a machine user (e.g., a computerconfigured by a software program to interact with the offering userdevice 130 or procuring user device 150), or any suitable combinationthereof (e.g., a human assisted by a machine or a machine supervised bya human). The offering user 132 is associated with the offering userdevice 130 and may be a user of the offering user device 130. Forexample, the offering user device 130 may be a desktop computer, avehicle computer, a tablet computer, a navigational device, a portablemedia device, a smart phone, or a wearable device (e.g., a smart watch,smart glasses, smart clothing, or smart jewelry) belonging to theoffering user 132. Likewise, the procuring user 152 is associated withthe procuring user device 150 and may be a user of the procuring userdevice 150. As an example, the procuring user device 150 may be adesktop computer, a vehicle computer, a tablet computer, a navigationaldevice, a portable media device, a smart phone, or a wearable device(e.g., a smart watch, smart glasses, smart clothing, or smart jewelry)belonging to the procuring user 152.

Any of the systems or machines (e.g., databases and devices) shown inFIG. 1 may be, include, or otherwise be implemented in a special-purpose(e.g., specialized or otherwise non-generic) computer that has beenmodified (e.g., configured or programmed by software, such as one ormore software modules of an application, operating system, firmware,middleware, or other program) to perform one or more of the functionsdescribed herein for that system or machine. For example, aspecial-purpose computer system able to implement any one or more of themethodologies described herein is discussed below with respect to FIG.10, and such a special-purpose computer may accordingly be a means forperforming any one or more of the methodologies discussed herein. Withinthe technical field of such special-purpose computers, a special-purposecomputer that has been modified by the structures discussed herein toperform the functions discussed herein is technically improved comparedto other special-purpose computers that lack the structures discussedherein or are otherwise unable to perform the functions discussedherein. Accordingly, a special-purpose machine configured according tothe systems and methods discussed herein provides an improvement to thetechnology of similar special-purpose machines.

As used herein, a “database” is a data storage resource and may storedata structured as a text file, a table, a spreadsheet, a relationaldatabase (e.g., an object-relational database), a triple store, ahierarchical data store, or any suitable combination thereof. Moreover,any two or more of the systems or machines illustrated in FIG. 1 may becombined into a single machine, and the functions described herein forany single system or machine may be subdivided among multiple systems ormachines.

The network 190 may be any network that enables communication between oramong systems, machines, databases, and devices (e.g., between theguided listing machine 110 and the offering user device 130).Accordingly, the network 190 may be a wired network, a wireless network(e.g., a mobile or cellular network), or any suitable combinationthereof. The network 190 may include one or more portions thatconstitute a private network, a public network (e.g., the Internet), orany suitable combination thereof. Accordingly, the network 190 mayinclude one or more portions that incorporate a local area network(LAN), a wide area network (WAN), the Internet, a mobile telephonenetwork (e.g., a cellular network), a wired telephone network (e.g., aplain old telephone system (POTS) network), a wireless data network(e.g., a WiFi network or WiMax network), or any suitable combinationthereof. Any one or more portions of the network 190 may communicateinformation via a transmission medium. As used herein, “transmissionmedium” refers to any intangible (e.g., transitory) medium that iscapable of communicating (e.g., transmitting) instructions for executionby a machine (e.g., by one or more processors of such a machine), andincludes digital or analog communication signals or other intangiblemedia to facilitate communication of such software.

FIG. 2 is a block diagram illustrating components of the guided listingmachine 110, according to some example embodiments. The guided listingmachine 110 is shown as including a request receiver 210, a datareceiver 220, an alert generator 230, and an alert presenter 240, allconfigured to communicate with each other (e.g., via a bus, sharedmemory, or a switch).

As shown in FIG. 2, the request receiver 210, the data receiver 220, andthe alert generator 230 may form all or part of an app 200 that isstored (e.g., installed) on the guided listing machine 110. Furthermore,one or more processors 299 (e.g., hardware processors, digitalprocessors, or any suitable combination thereof) may be included (e.g.,temporarily or permanently) in the app 200, request receiver 210, datareceiver 220, alert generator 230, alert presenter 240, or any suitablecombination thereof.

Any one or more of the components (e.g., modules) described herein maybe implemented using hardware alone (e.g., one or more of the processors299) or a combination of hardware and software. For example, anycomponent described herein may physically include an arrangement of oneor more of the processors 299 (e.g., a subset of or among the processors299) configured to perform the operations described herein for thatcomponent. As another example, any component described herein mayinclude software, hardware, or both, that configure an arrangement ofone or more of the processors 299 to perform the operations describedherein for that component. Accordingly, different components describedherein may include and configure different arrangements of theprocessors 299 at different points in time or a single arrangement ofthe processors 299 at different points in time. Each component (e.g.,module) described herein is an example of a means for performing theoperations described herein for that component. Moreover, any two ormore components described herein may be combined into a singlecomponent, and the functions described herein for a single component maybe subdivided among multiple components. Furthermore, according tovarious example embodiments, components described herein as beingimplemented within a single system or machine (e.g., a single device)may be distributed across multiple systems or machines (e.g., multipledevices). The processors 299 may further communicate with one or more ofthe structural components detailed above, including the request receiver210, the data receiver 220, the alert generator 230, and the alertpresenter 240.

FIGS. 3-5 are flowcharts illustrating operations of the guided listingmachine 110 in performing a method 300 of guiding a listing andproviding authenticity support, according to some example embodiments.The guided listing machine 110 may include components (e.g., modules)described above with respect to FIG. 2, one or more processors (e.g.,microprocessors or other hardware processors), or any suitablecombination thereof. As shown in FIG. 3, the method 300 includesoperations 310, 320, 330, 340, and 350.

In operation 310, the request receiver 210 receives a request to publishavailability of a candidate specimen of a product, the request receivedfrom the offering user device 130 over a network. Various methods can beused to receive information from the offering user 132 and associate theinformation as related to a product. For example, the offering user 132may submit one or more keywords related to a product, a title of theproduct, a picture of a product, or any suitable combination thereof. Inanother example embodiment, the offering user 132 may select the productfrom a list of products.

In an example embodiment, the offering user 132 desires to list “Bolt”running shoes that are part of the “Victory Collection” for sale. Theoffering user 132 submits a request to the app 200 to publish a listingof the product, the request made using a drop down menu with variousproducts. In another embodiment, the offering user 132 inputs the title“Bolt: Victory Collection” in a text box, and the request receiver 220matches the title to the product. In another example embodiment, theoffering user 132 inputs the keywords “Bolt Shoe Victory” in a text boxand the request receiver 220 presents various products related to thekeywords. In another example embodiment, the offering user 132 inputs“Shoe” and then selects the title “Bolt: Victory Collection” from a dropdown menu of products related to “Shoe.”

In operation 320, the data receiver 220, responsive to the requestreceiver 210 receiving the request to publish availability of theproduct, accesses (e.g., retrieves) an authenticity criterion mapped tothe product, the authenticity criterion describing a reference detail.The reference detail, as mentioned previously, is any characteristicthat is visually apparent on a product. In some example embodiments, theauthenticity criterion is accessed from the product database 115. Inalternative example embodiments, the data receiver 220 may access theauthenticity criterion from a database outside the network-based system105 over the network 190. More than one authenticity criterion may bemapped to the product.

An authenticity criterion includes a rule that any specimen of aparticular product exhibits a reference detail, such as a particularphysical detail. The reference detail includes, but is not limited, tophysical characteristics of a product that are visibly present. Forexample, an authenticity criterion for a brand of purse may indicatethat all purses of this brand exhibit the reference detail of havinggold, black, and blue thread stitching on the handle of the purse. Onlypurses that exhibit gold, black and blue stitching on their handleswould fulfill this authenticity criterion. A similar purse having black,gold, and green thread stitching on the handle would not fulfill thiscriterion and may be a counterfeit product or an entirely differentproduct altogether.

Continuing with the previous running shoe example, the request receiver210 may collect data indicating that the offering user 132 desires tolist a “Bolt: Victory Collection” running shoe for sale. The datareceiver 220 may access a data structure such as the product database115 and retrieve any authenticity criteria that are mapped to the “Bolt:Victory Collection” product, the authenticity criteria describingreference details that are visually apparent in an authentic specimen ofthe product. In this example, the data receiver 220 accesses andretrieves an authenticity criterion describing a particular pattern oftoe stitching that all “Bolt: Victory Collection” products exhibit.

In operation 330, the data receiver 220, responsive to accessing theauthenticity criterion, further accesses a reference image depicting atleast a portion of a reference specimen of the product that exhibits thereference detail. The reference detail exhibited by the referencespecimen is adequate to fulfill the authenticity criterion previouslyreceived. In some example embodiments the data receiver 220 can accessthe reference image within an image database 116, the image database 116containing multiple images exhibiting reference details that fulfillauthenticity criteria for multiple products. In alternative exampleembodiments, the data receiver 220 may access the candidate image from adatabase over the network 190, but outside the network-based system 105.

Continuing the above running shoe example, the data receiver 220accesses the image database 116 and retrieve a reference image thatdepicts the toe stitching of the shoe reference detail. There may bemultiple reference images depicting various parts of the “Bolt: VictoryCollection” shoe within the image database 116. The data receiver 220accesses the image database 220 and accesses a reference image thatdepicts the detail of the toe stitching. Additionally, the toe stitchingreference detail depicted in the reference image fulfills theauthenticity criterion.

In operation 340, the alert generator 230, responsive to the datareceiver 220 accessing the reference image in operation 330, generatesan alert containing both the reference image that depicts the referencedetail as well as a suggestion that the offering user 132 submit thecandidate image. The suggestion, when presented, notifies the offeringuser 132 that the candidate image should be a similar depiction of theproduct, in that the reference detail displayed in the reference imageshould be similar to a candidate detail displayed in the candidateimage. In this way, the alert may prompt the offering user 132 to submita candidate image displaying a candidate detail that fulfills theauthenticity criterion, the candidate detail visually apparent on thecandidate specimen that the offering user 132 desires to publishavailability for.

Continuing the running shoe example, the alert generator 230 may pairthe reference image of the “Bolt: Victory Collection” that depicts thetoe stitching with a message that suggests that the offering user 132submit a candidate image that depicts the toe region of the shoe theoffering user 132 is trying to sell. For example, the alert generator230 may generate language such as “It would be helpful for buyers if youadd an image of the toe region of the product to show detail of thestitching.”

In operation 350, the alert presenter 240, in response to the alertgenerator 230 generating an alert, presents the alert to the offeringuser 132. In an example embodiment, the alert presenter 240 communicateswith the offering user device 130 to cause the offering user device 130to present the alert to the offering user 132. In a further exampleembodiment, the alert presenter 240 may be configured to present thealert containing both the reference image and the suggestion to theoffering user 132, such that the offering user 132 can view thereference image and the suggestion at the same time.

Continuing with the running shoe example, the alert presenter 240communicates with the offering user device 130 and causes the offeringuser device 130 to present the alert to the offering user 132.Therefore, after submitting a request to publish availability of the“Bolt: Victory Collection” shoe, the offering user 132 may be presentedwith a suggestion that the offering user 132 upload a candidate image ofthe toe stitching on the shoe for sale, as well as a reference imagedepicting how the toe stitching should appear.

In some example embodiments, method 300 includes further operations,such as operations 410, 420, and 430 as displayed in FIG. 4. Inoperation 410, the data receiver 220, responsive to the alert presenter240 presenting the offering user 132 with the alert containing thereference image and the suggestion, retrieves a candidate image from theoffering user 132, the candidate image depicting a portion of thecandidate specimen (the specimen of the product that the offering user132 is listing) and the candidate detail that fulfills the authenticitycriterion. In an example embodiment, the data receiver 220 causes theoffering user device 130 to provide the offering user 132 with a userform to upload one or more candidate images to the guided listingmachine 110 over the network 190. The data receiver 220 can store theone or more candidate images on a memory structure accessible by theguided listing machine 110, such as the image database 115.

In another example embodiment, the data receiver 220 provides theoffering user 132 with a secure messaging service to submit one or moreimages. In another example embodiment, the data receiver 220 can operatein conjunction with the alert presenter 240 to provide the offering user132 with the user form or the secure messaging service, particularlywhere the alert presenter 240 is configured to present messages to theoffering user 132 on the offering user device 130.

In operation 420, the alert presenter 240, in response to the datareceiver 220 retrieving a candidate image, displays a confirmationmessage to the offering user 132. The confirmation message may bedisplayed on the offering user device 130 and may contain language toinform the offering user 132 of a successful submission of one or morecandidate image. Continuing the example above, in response to theoffering user 132 submitting an image depicting the “Bolt: VictoryCollection” shoe, the alert presenter 420 may cause a message to appearon the offering user device 130 reading: “Thank you for uploading apicture of the toe stitching.”

In operation 430, alert presenter 240 can further display the referenceimage and at least one candidate image on the offering user device 130,the offering user device 130 displaying the reference image and thecandidate image at the same time. For example, the offering user device130 may have multiple bounded windows. The alert presenter 240 cancommunicate instructions to the offering user device 130, theinstructions causing the offering user device 130 to display thereference image and the candidate image in the same bounded window. Thismethod of display allows the offering user 132 the option to compare thereference detail to the candidate detail. The method 300 thereforeallows the offering user 132 the ability to judge whether or not thecandidate detail fulfills the authenticity criterion. Continuing withthe running shoe example, the alert presenter 240 may present toestitching on the reference image of the “Bolt: Victory Collection” shoein the same window as the candidate image that the offering user 132 hasuploaded.

In some example embodiments, the method 300 includes further operations,such as operations 510, 520, 530, 540, and 550 as displayed in FIG. 5.In operation 510, the network-based system 105, responsive to receivingone or more images uploaded by the offering user 132 in operation 410,adjusts a rank of a candidate specimen based on various factors,including factors described in operations 520, 530, 540, and 550. Inadjusting the rank of a candidate specimen, the network-based system 105may use various machines, data structures and processors connected tothe network 190, such as the components of the guided listing machine110.

The rank of a candidate specimen, as defined herein, is an ordering ofproduct specimens that are available for procurement, the ordering beingpresentable to the procuring user 152. The ordering may further beviewable to the procuring user 152 in a list format on a device, such asthe procuring user device 150.

In operation 520, the network-based system 105 adjusts the rank of acandidate specimen in response to receiving the candidate image from theoffering user 132, as described in operation 420. In some exampleembodiments, the network-based system 105 adjusts the rank of thecandidate specimen upward if the offering user 132 has submitted acandidate image.

Continuing with the running shoe example, the product availabilitypublished for the “Bolt: Victory Collection” shoe may be ranked higherif the product availability includes a candidate image that displaysdetail of the toe stitching. The network-based system 105 can order thelisting for the candidate specimen in such a way that it is more likelyto be viewed by the procuring user 152. The procuring user 152 mayfurther be more likely to consider purchasing the shoe, not only becauseit is ranked higher, but because the procuring user 152 has theopportunity to view the candidate image and assess the authenticity ofthe candidate detail of the candidate specimen, in this case, the toestitching.

In operation 520, the network-based system 105 can adjust the rank ofthe candidate specimen in response to the item being part of acollection. In some example embodiments, the network-based system 105detects a collection identifier within the data of the productavailability. The network-based system 105 can adjust the rank upward ordownward based on a collection identifier depending on various factors,including the likelihood that counterfeit products from a collection arepublished as authentic products.

Continuing with the running shoe example, if the offering user 132 liststhe “Bolt: Victory Collection” shoe as part of the “Victory Collection.”The network-based system 105 detects a collection identifier associatedwith the listing and determines that the “Victory Collection” is ahighly counterfeited collection. Since the offering user 132 hasuploaded the candidate image at operation 420, the network-based system105 may adjust the rank of the offering user's 132 listing upwardbecause the candidate image helps verify a highly counterfeited item.

In operation 540, the network-based system 105 adjusts the rank of thecandidate specimen in response to a record of the offering user's 132history of uploading images. In some example embodiments, network-basedsystem 105 accesses the user history database 117 to assess whether theoffering user 132 that is publishing the availability of an item has aprevious history of providing candidate images with item listings. Thenetwork-based system 105 may adjust the rank of a candidate specimenupward if the offering user 132 has a history of always includingcandidate images with items, indicating that the previous items arelikely authentic and the offering user 132 is more likely to listauthentic items.

In operation 550, the network-based system 105 determines that thecandidate image provided by the offering user 132 is a copy of an imagealready within a database and adjusts the rank of the candidate specimenbased on this determination. Examples of the database include theproduct database 115, the image database 116, and the user historydatabase 117. In some example embodiments, a copy identifier may bepresent within the data of the candidate image, the copy identifiermatching another copy identifier present in the data of an image in thedatabase. The network-based system 105 adjusts the rank of the candidatespecimen down in response to the copy identifier being present in thecandidate image, because a candidate image should not be one that isalready in the database, indicating the candidate specimen ispotentially a counterfeit.

Continuing with the running shoe example, the offering user 132 may copythe reference image for the “Bolt: Victory Collection” shoe presented inthe alert at operation 350 and upload the same image as the candidateimage. The network-based system 105 can detect the copy identifier inthe data of the candidate image and adjust the rank of the candidatespecimen down, because the offering user 132 has not provided anoriginal candidate image and the candidate specimen has a higherlikelihood of being a counterfeit.

FIG. 6 is an illustration showing an example embodiment of operation310, where the request receiver accesses the request to publishavailability of the candidate specimen of the product item. FIG. 6additionally continues the previous running shoe example, in which theoffering user 132, requests to publish the availability of a specimen(e.g., candidate specimen) of the “Bolt: Victory Collection” product forsale.

In this example, the offering user device 130 is shown displaying a userinterface 620, which may be a graphical user interface. Displayed on theuser interface 620 in a product window 630 is a sample picture of theproduct that the offering user 132 wishes to list, as well as a textdescription of the product. The offering user device 130 may furthershow a query window 640 that prompts the offering user 132 with aquestion and an interactive bar 650 that allows the offering user 132 toselect an action from among multiple actions. In this example, theinteractive bar 650 allows the offering user 132 to select “Publish” toinitiate the request to publish the availability of the specimen of theproduct.

FIG. 7 is an illustration that continues the above example, showing anexample embodiment of operation 350 where the offering user 132 ispresented with an alert on the offering user device 130, the alertcontaining a reference image and a suggestion to submit a candidateimage. In the example, the product window 630 for the “Bolt: VictoryCollection” shoe is still present. In addition, there is a suggestionwindow 710, containing a suggestion that the offering user 132 include acandidate image. Additionally, a message appears in suggestion window710 that communicates a benefit of including a candidate image,specifically that “sellers of “Bolt” brand shoes are 87% more likely tosell if they include an authenticity picture.”

Additionally, FIG. 7 depicts a reference window 720 containing thereference image that that depicts the “toe stitching” reference detailthat fulfills the reference criterion. Finally, the interactive bar 650has been altered to include an option that says “Upload Image.” Anoffering user 132 can select this option to be presented with a methodto upload a candidate image, the method including using an upload formor a secure message.

FIG. 8 is an illustration that continues the above example, showing anexample embodiment of operation 430 where the reference image and thecandidate image are displayed in the same window. Included in theillustration is a title window 810 to communicate to the offering user132 the reference detail that the candidate image should fulfill, hereit is the “toe stitching” detail. Comparison window 820 contains twoimages, first, the candidate image 830, and second, the reference image840. These images are presented in the same window so the offering user132 can easily compare the images and judge whether the candidate detailis adequately shown to fulfill the authenticity criterion. Additionallyin this example, the product window 630 has changed to only include textand the query window 640 has changed to ask “Accept Snapshot?” for theoffering user 132 to verify that the representation of the candidatedetail is adequate. The “submit” button on the interactive bar 650allows the offering user 132 to accept the upload of the snapshot andcontinue with the publication of the listing.

FIG. 9 is an illustration that continues the above example, showing anexample embodiment of operation 540 where a rank is adjusted based onthe presence of a candidate image. The illustration includes procuringuser device 150 that is displayed to the procuring user 152. In theillustration, a first offer window 920 is included with a second offerwindow 930 and a third offer window 940. In response to a search by theprocuring user 152 within the search text box 910, an ordering of offersis presented to the procuring user 152. In this example, first offerwindow 920 and second offer window 930 are ranked higher than thirdoffer window 940 because the first and second offers include a candidateimage whereas the third offer does not include a candidate image. Forthis reason, the first and second offers receive a higher rank than thethird offer and the first offer window 920 and the second offer window930 receive a higher ordering and are viewed by the procuring user 152before the third offer window 940.

According to various example embodiments, one or more of themethodologies described herein may facilitate guiding a listing andproviding authenticity support. Moreover, one or more of themethodologies described herein may facilitate adjusting a rank of acandidate specimen.

When these effects are considered in aggregate, one or more of themethodologies described herein may obviate a need for certain efforts orresources that otherwise would be involved in guiding a listing andproviding authenticity support. Efforts expended by the guided listingmachine 110 in guiding a listing and providing authenticity support maybe reduced by use of (e.g., reliance upon) a special-purpose machinethat implements one or more of the methodologies described herein.Computing resources used by one or more systems or machines (e.g.,within the network environment 100) may similarly be reduced (e.g.,compared to systems or machines that lack the structures discussedherein or are otherwise unable to perform the functions discussedherein). Examples of such computing resources include processor cycles,network traffic, computational capacity, main memory usage, graphicsrendering capacity, graphics memory usage, data storage capacity, powerconsumption, and cooling capacity.

FIG. 10 is a block diagram illustrating components of a machine 1000,according to some example embodiments, able to read instructions 1024from a machine-readable medium 1022 (e.g., a non-transitorymachine-readable medium, a machine-readable storage medium, acomputer-readable storage medium, or any suitable combination thereof)and perform any one or more of the methodologies discussed herein, inwhole or in part. Specifically, FIG. 10 shows the machine 1000 in theexample form of a computer system (e.g., a computer) within which theinstructions 1024 (e.g., software, a program, an application, an applet,an app, or other executable code) for causing the machine 1000 toperform any one or more of the methodologies discussed herein may beexecuted, in whole or in part.

In other example embodiments, the machine 1000 operates as a standalonedevice or may be communicatively coupled (e.g., networked) to othermachines. In a networked deployment, the machine 1000 may operate in thecapacity of a server machine or a client machine in a server-clientnetwork environment, or as a peer machine in a distributed (e.g.,peer-to-peer) network environment. The machine 1000 may be a servercomputer, a client computer, a personal computer (PC), a tabletcomputer, a laptop computer, a netbook, a cellular telephone, a smartphone, a set-top box (STB), a personal digital assistant (PDA), a webappliance, a network router, a network switch, a network bridge, or anymachine capable of executing the instructions 1024, sequentially orotherwise, that specify actions to be taken by that machine. Further,while only a single machine is illustrated, the term “machine” shallalso be taken to include any collection of machines that individually orjointly execute the instructions 1024 to perform all or part of any oneor more of the methodologies discussed herein.

The machine 1000 includes a processor 1002 (e.g., one or more centralprocessing units (CPUs), one or more graphics processing units (GPUs),one or more digital signal processors (DSPs), one or more applicationspecific integrated circuits (ASICs), one or more radio-frequencyintegrated circuits (RFICs), or any suitable combination thereof), amain memory 1004, and a static memory 1006, which are configured tocommunicate with each other via a bus 1008. The processor 1002 containssolid-state digital microcircuits (e.g., electronic, optical, or both)that are configurable, temporarily or permanently, by some or all of theinstructions 1024 such that the processor 1002 is configurable toperform any one or more of the methodologies described herein, in wholeor in part. For example, a set of one or more microcircuits of theprocessor 1002 may be configurable to execute one or more modules (e.g.,software modules) described herein. In some example embodiments, theprocessor 1002 is a multicore CPU (e.g., a dual-core CPU, a quad-coreCPU, an 8-core CPU, or a 128-core CPU) within which each of multiplecores behaves as a separate processor that is able to perform any one ormore of the methodologies discussed herein, in whole or in part.Although the beneficial effects described herein may be provided by themachine 1000 with at least the processor 1002, these same beneficialeffects may be provided by a different kind of machine that contains noprocessors (e.g., a purely mechanical system, a purely hydraulic system,or a hybrid mechanical-hydraulic system), if such a processor-lessmachine is configured to perform one or more of the methodologiesdescribed herein.

The machine 1000 may further include a graphics display 1010 (e.g., aplasma display panel (PDP), a light emitting diode (LED) display, aliquid crystal display (LCD), a projector, a cathode ray tube (CRT), orany other display capable of displaying graphics or video). The machine1000 may also include an alphanumeric input device 1012 (e.g., akeyboard or keypad), a pointer input device 1014 (e.g., a mouse, atouchpad, a touchscreen, a trackball, a joystick, a stylus, a motionsensor, an eye tracking device, a data glove, or other pointinginstrument), a data storage 1016, an audio generation device 1018 (e.g.,a sound card, an amplifier, a speaker, a headphone jack, or any suitablecombination thereof), and a network interface device 1020.

The data storage 1016 (e.g., a data storage device) includes themachine-readable medium 1022 (e.g., a tangible and non-transitorymachine-readable storage medium) on which are stored the instructions1024 embodying any one or more of the methodologies or functionsdescribed herein. The instructions 1024 may also reside, completely orat least partially, within the main memory 1104, within the staticmemory 1006, within the processor 1002 (e.g., within the processor'scache memory), or any suitable combination thereof, before or duringexecution thereof by the machine 1000. Accordingly, the main memory1004, the static memory 1006, and the processor 1002 may be consideredmachine-readable media (e.g., tangible and non-transitorymachine-readable media). The instructions 1024 may be transmitted orreceived over the network 190 via the network interface device 1020. Forexample, the network interface device 1020 may communicate theinstructions 1024 using any one or more transfer protocols (e.g.,hypertext transfer protocol (HTTP)).

In some example embodiments, the machine 1000 may be a portablecomputing device (e.g., a smart phone, a tablet computer, or a wearabledevice), and may have one or more additional input components 1030(e.g., sensors or gauges). Examples of such input components 1030include an image input component (e.g., one or more cameras), an audioinput component (e.g., one or more microphones), a direction inputcomponent (e.g., a compass), a location input component (e.g., a globalpositioning system (GPS) receiver), an orientation component (e.g., agyroscope), a motion detection component (e.g., one or moreaccelerometers), an altitude detection component (e.g., an altimeter), abiometric input component (e.g., a heartrate detector or a bloodpressure detector), and a gas detection component (e.g., a gas sensor).Input data gathered by any one or more of these input components may beaccessible and available for use by any of the modules described herein.

As used herein, the term “memory” refers to a machine-readable mediumable to store data temporarily or permanently and may be taken toinclude, but not be limited to, random-access memory (RAM), read-onlymemory (ROM), buffer memory, flash memory, and cache memory. While themachine-readable medium 1022 is shown in an example embodiment to be asingle medium, the term “machine-readable medium” should be taken toinclude a single medium or multiple media (e.g., a centralized ordistributed database, or associated caches and servers) able to storeinstructions. The term “machine-readable medium” shall also be taken toinclude any medium, or combination of multiple media, that is capable ofstoring the instructions 1024 for execution by the machine 1000, suchthat the instructions 1024, when executed by one or more processors ofthe machine 1000 (e.g., processor 1002), cause the machine 1000 toperform any one or more of the methodologies described herein, in wholeor in part. Accordingly, a “machine-readable medium” refers to a singlestorage apparatus or device, as well as cloud-based storage systems orstorage networks that include multiple storage apparatus or devices. Theterm “machine-readable medium” shall accordingly be taken to include,but not be limited to, one or more tangible and non-transitory datarepositories (e.g., data volumes) in the example form of a solid-statememory chip, an optical disc, a magnetic disc, or any suitablecombination thereof. A “non-transitory” machine-readable medium, as usedherein, specifically does not include propagating signals per se. Insome example embodiments, the instructions 1024 for execution by themachine 1000 may be communicated by a carrier medium. Examples of such acarrier medium include a storage medium (e.g., a non-transitorymachine-readable storage medium, such as a solid-state memory, beingphysically moved from one place to another place) and a transient medium(e.g., a propagating signal that communicates the instructions 1024).

Certain example embodiments are described herein as including modules.Modules may constitute software modules (e.g., code stored or otherwiseembodied in a machine-readable medium or in a transmission medium),hardware modules, or any suitable combination thereof. A “hardwaremodule” is a tangible (e.g., non-transitory) physical component (e.g., aset of one or more processors) capable of performing certain operationsand may be configured or arranged in a certain physical manner. Invarious example embodiments, one or more computer systems or one or morehardware modules thereof may be configured by software (e.g., anapplication or portion thereof) as a hardware module that operates toperform operations described herein for that module.

In some example embodiments, a hardware module may be implementedmechanically, electronically, hydraulically, or any suitable combinationthereof. For example, a hardware module may include dedicated circuitryor logic that is permanently configured to perform certain operations. Ahardware module may be or include a special-purpose processor, such as afield programmable gate array (FPGA) or an ASIC. A hardware module mayalso include programmable logic or circuitry that is temporarilyconfigured by software to perform certain operations. As an example, ahardware module may include software encompassed within a CPU or otherprogrammable processor. It will be appreciated that the decision toimplement a hardware module mechanically, hydraulically, in dedicatedand permanently configured circuitry, or in temporarily configuredcircuitry (e.g., configured by software) may be driven by cost and timeconsiderations.

Accordingly, the phrase “hardware module” should be understood toencompass a tangible entity that may be physically constructed,permanently configured (e.g., hardwired), or temporarily configured(e.g., programmed) to operate in a certain manner or to perform certainoperations described herein. Furthermore, as used herein, the phrase“hardware-implemented module” refers to a hardware module. Consideringexample embodiments in which hardware modules are temporarily configured(e.g., programmed), each of the hardware modules need not be configuredor instantiated at any one instance in time. For example, where ahardware module includes a CPU configured by software to become aspecial-purpose processor, the CPU may be configured as respectivelydifferent special-purpose processors (e.g., each included in a differenthardware module) at different times. Software (e.g., a software module)may accordingly configure one or more processors, for example, to becomeor otherwise constitute a particular hardware module at one instance oftime and to become or otherwise constitute a different hardware moduleat a different instance of time.

Hardware modules can provide information to, and receive informationfrom, other hardware modules. Accordingly, the described hardwaremodules may be regarded as being communicatively coupled. Where multiplehardware modules exist contemporaneously, communications may be achievedthrough signal transmission (e.g., over circuits and buses) between oramong two or more of the hardware modules. In example embodiments inwhich multiple hardware modules are configured or instantiated atdifferent times, communications between such hardware modules may beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware modules have access.For example, one hardware module may perform an operation and store theoutput of that operation in a memory (e.g., a memory device) to which itis communicatively coupled. A further hardware module may then, at alater time, access the memory to retrieve and process the stored output.Hardware modules may also initiate communications with input or outputdevices, and can operate on a resource (e.g., a collection ofinformation from a computing resource).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions describedherein. As used herein, “processor-implemented module” refers to ahardware module in which the hardware includes one or more processors.Accordingly, the operations described herein may be at least partiallyprocessor-implemented, hardware-implemented, or both, since a processoris an example of hardware, and at least some operations within any oneor more of the methods discussed herein may be performed by one or moreprocessor-implemented modules, hardware-implemented modules, or anysuitable combination thereof.

Moreover, such one or more processors may perform operations in a “cloudcomputing” environment or as a service (e.g., within a “software as aservice” (SaaS) implementation). For example, at least some operationswithin any one or more of the methods discussed herein may be performedby a group of computers (e.g., as examples of machines that includeprocessors), with these operations being accessible via a network (e.g.,the Internet) and via one or more appropriate interfaces (e.g., anapplication program interface (API)). The performance of certainoperations may be distributed among the one or more processors, whetherresiding only within a single machine or deployed across a number ofmachines. In some example embodiments, the one or more processors orhardware modules (e.g., processor-implemented modules) may be located ina single geographic location (e.g., within a home environment, an officeenvironment, or a server farm). In other example embodiments, the one ormore processors or hardware modules may be distributed across a numberof geographic locations.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures and theirfunctionality presented as separate components and functions in exampleconfigurations may be implemented as a combined structure or componentwith combined functions. Similarly, structures and functionalitypresented as a single component may be implemented as separatecomponents and functions. These and other variations, modifications,additions, and improvements fall within the scope of the subject matterherein.

Some portions of the subject matter discussed herein may be presented interms of algorithms or symbolic representations of operations on datastored as bits or binary digital signals within a memory (e.g., acomputer memory or other machine memory). Such algorithms or symbolicrepresentations are examples of techniques used by those of ordinaryskill in the data processing arts to convey the substance of their workto others skilled in the art. As used herein, an “algorithm” is aself-consistent sequence of operations or similar processing leading toa desired result. In this context, algorithms and operations involvephysical manipulation of physical quantities. Typically, but notnecessarily, such quantities may take the form of electrical, magnetic,or optical signals capable of being stored, accessed, transferred,combined, compared, or otherwise manipulated by a machine. It isconvenient at times, principally for reasons of common usage, to referto such signals using words such as “data,” “content,” “bits,” “values,”“elements,” “symbols,” “characters,” “terms,” “numbers,” “numerals,” orthe like. These words, however, are merely convenient labels and are tobe associated with appropriate physical quantities.

Unless specifically stated otherwise, discussions herein using wordssuch as “accessing,” “processing,” “detecting,” “computing,”“calculating,” “determining,” “generating,” “presenting,” “displaying,”or the like refer to actions or processes performable by a machine(e.g., a computer) that manipulates or transforms data represented asphysical (e.g., electronic, magnetic, or optical) quantities within oneor more memories (e.g., volatile memory, non-volatile memory, or anysuitable combination thereof), registers, or other machine componentsthat receive, store, transmit, or display information. Furthermore,unless specifically stated otherwise, the terms “a” or “an” are hereinused, as is common in patent documents, to include one or more than oneinstance. Finally, as used herein, the conjunction “or” refers to anon-exclusive “or,” unless specifically stated otherwise.

1. A method performed by one or more hardware processors, comprising:receiving, from a computing device, a request to publish a listing of aphysical item; first determining the physical item is included in acollection; second determining, based on the physical item beingincluded in the collection, that a probability that the physical item isa counterfeit item meets a criterion; causing, in response to the seconddetermining, display of a message on the computing device, the messagerequesting submission of an image depicting a portion of the physicalitem; receiving, in response to the message, an image; searching animage database, the image database including reference images of theportion; third determining, based on the searching, that the receivedimage is a copy of an image in the image database; and adjusting a rankof the listing within a plurality of search results based on the thirddetermining.
 2. The method of claim 1, wherein the adjusting of the rankreduces the rank of the listing in response to determining that thereceived image is a copy.
 3. The method of claim 1, wherein the thirddetermining that the received image is a copy comprises detecting apresence of a copy identifier in the received image, wherein the thirddetermining that the received image is a copy is based on the detecting.4. The method of claim 1, further comprising causing, on the computingdevice, presentation of a confirmation message that the image wassuccessfully submitted.
 5. The method of claim 1, wherein the message isgenerated to include instructions for uploading an image that depictsthe portion of the physical item.
 6. The method of claim 1, furthercomprising: determining a user associated with the computing device; anddetermining whether the user provided additional images in response toadditional messages, wherein the adjusting of the rank is based onwhether the user has provided additional images.
 7. The method of claim1, further comprising receiving an image of the item from the computingdevice, wherein determining the item is part of the collection comprisesdetecting an identifier indicative of the collection in the image of theitem.
 8. A system, comprising: hardware processing circuitry; and one ormore hardware memories storing instructions that when executed configurethe hardware processing circuitry to perform operations comprising:receiving, from a computing device, a request to publish a listing of aphysical item; first determining the physical item is included in acollection; second determining, based on the physical item beingincluded in the collection, that a probability that the physical item isa counterfeit item meets a criterion; causing, in response to the seconddetermining, display of a message on the computing device, the messagerequesting submission of an image depicting a portion of the physicalitem; receiving, in response to the message, an image; searching animage database, the image database including reference images of theportion; third determining, based on the searching, that the receivedimage is a copy of an image in the image database; and adjusting a rankof the listing within a plurality of search results based on the thirddetermining.
 9. The system of claim 8, wherein the adjusting of the rankreduces the rank of the listing in response to determining that thereceived image is a copy.
 10. The system of claim 8, wherein the thirddetermining that the received image is a copy comprises detecting apresence of a copy identifier in the received image, wherein the thirddetermining that the received image is a copy is based on the detecting.11. The system of claim 8, the operations further comprising causing, onthe computing device, presentation of a confirmation message that theimage was successfully submitted.
 12. The system of claim 8, wherein themessage is generated to include instructions for uploading an image thatdepicts the portion of the physical item.
 13. The system of claim 8, theoperations further comprising: determining a user associated with thecomputing device; and determining whether the user provided additionalimages in response to additional messages, wherein the adjusting of therank is based on whether the user has provided additional images. 14.The system of claim 8, the operations further comprising receiving animage of the item from the computing device, wherein determining theitem is part of the collection comprises detecting an identifierindicative of the collection in the image of the item.
 15. Anon-transitory computer readable storage medium comprising instructionsthat when executed configure hardware processing circuitry to performoperations comprising: receiving, from a computing device, a request topublish a listing of a physical item; first determining the physicalitem is included in a collection; second determining, based on thephysical item being included in the collection, that a probability thatthe physical item is a counterfeit item meets a criterion; causing, inresponse to the second determining, display of a message on thecomputing device, the message requesting submission of an imagedepicting a portion of the physical item; receiving, in response to themessage, an image; searching an image database, the image databaseincluding reference images of the portion; third determining, based onthe searching, that the received image is a copy of an image in theimage database; and adjusting a rank of the listing within a pluralityof search results based on the third determining.
 16. The non-transitorycomputer readable storage medium of claim 15, wherein the adjusting ofthe rank reduces the rank of the listing in response to determining thatthe received image is a copy.
 17. The non-transitory computer readablestorage medium of claim 15, wherein the third determining that thereceived image is a copy comprises detecting a presence of a copyidentifier in the received image, wherein the third determining that thereceived image is a copy is based on the detecting.
 18. Thenon-transitory computer readable storage medium of claim 15, wherein themessage is generated to include instructions for uploading an image thatdepicts the portion of the physical item.
 19. The non-transitorycomputer readable storage medium of claim 15, further comprising:determining a user associated with the computing device; and determiningwhether the user provided additional images in response to additionalmessages, wherein the adjusting of the rank is based on whether the userhas provided additional images.
 20. The non-transitory computer readablestorage medium of claim 15, further comprising receiving an image of theitem from the computing device, wherein determining the item is part ofthe collection comprises detecting an identifier indicative of thecollection in the image of the item.